This description relates to facilitating vehicle driving and vehicle self-driving.
Typical driving of vehicles by people and self-driving of vehicles using technology present opportunities and risks. Many of the perils are associated with how the vehicle is driven in light of the state of the vehicle and the state of the environment, including other vehicles and obstacles.
Normally a human driver who is driving a vehicle is able to control its operation so that the vehicle proceeds safely and reliably to a destination on, for example, a road network shared with other vehicles and pedestrians, while complying with applicable rules of the road. For a self-driving vehicle, a sequence of control actions can be generated based on real-time sensor data, geographic data (such as maps), regulatory/normative data (rules of the road), and historical information (such as traffic patterns) to enable the vehicle to proceed in such a manner.
It can be useful to monitor the performance of a human driver of a vehicle for safety and other reasons.
We use the term self-driving vehicles broadly to include, for example, any mobile device designed to carry passengers or objects or both from one or more pick-up locations to one or more drop-off locations, without requiring direct control or supervision by a human operator, for example, without requiring a human operator to be able to take over control responsibility at any time. Some examples of self-driving vehicles are self-driving road vehicles, self-driving off-road vehicles, self-driving cars, self-driving buses, self-driving vans or trucks, drones, or aircraft, among others.
We use the term regulatory data (or sometimes, the term rules of operation) broadly to include, for example, regulations, laws, and formal or informal rules governing the behavior patterns of users of devices, such as road users including vehicle drivers. These include rules of the road as well as best practices and passenger or operator preferences, described with similar precision and depth. We use the term historical information broadly to include, for example statistical data on behavior patterns of road users, including pedestrians, and cyclists, in each case possibly as a function of location, time of day, day of the week, seasonal and weather data, or other relevant features, or combinations of them.